Smartling Translation

Key Takeaways

• Smartling translation is built around a cloud translation management system, workflow automation, and project control.
• Smartling focuses on moving content through a managed localization process, while LILT focuses on adaptive AI that learns from professional linguists in real time.
• Both platforms aim to improve translation quality, but they use different approaches to ai translation, quality assurance, and translation management.
• For project managers, the real evaluation is simple: translation fast at scale, consistent multilingual content, and less manual effort.
• This guide is for localization leaders, project managers, and content teams evaluating Smartling translation and alternatives.

What Is Smartling Translation?

Smartling is a cloud-based Translation Management System designed to streamline localization. As translation management software, it helps companies manage global content for a website, mobile apps, product UI, support documents, and marketing campaigns in one platform.

Smartling’s core idea is to automate translation with connectors, workflow rules, a browser-based cat tool, and centralized project management. Smartling offers translation services and language services alongside software, and it is often compared with LILT when teams modernize their localization stack.

This article is written from LILT’s perspective: Smartling is strong in management, control, and integrations, while adaptive AI platforms can add value when teams want machine learning to improve quality as translators work.

How the Smartling Translation Process Works

The Smartling translation process usually includes content intake, workflow routing, translation, review, and delivery of translated content. Smartling automates the entire translation process, and Smartling supports automated workflows to efficiently manage translation projects.

Project managers configure workflows, assign tasks, grant access, and monitor each project instead of relying on email chains. Translation Memory stores previous translations in a centralized database. Centralized glossaries and style guides ensure brand consistency across translations.

Smartling emphasizes quality assurance through automated checks, review steps, and LQA rather than a fully adaptive model. Translation quality and speed still depend on setup, terminology, reviewers, and experienced professional translators.

Automation, Integrations, and Translation Fast

Smartling’s automation mainly moves content between systems and workflows. Smartling automates 99% of translation processes, and Smartling eliminates 90% of manual effort in translation, according to vendor claims.

Smartling integrates with 50+ pre-built connectors and APIs. Smartling's platform supports 50+ pre-built integrations, and Smartling automates content ingestion with pre-built integrations. Smartling supports integration with CMSs like WordPress and Drupal, plus Salesforce, Marketo, HubSpot, google drive, Git repositories, and more.

Smartling integrates with code storage systems like GitHub and Bitbucket. Smartling's platform supports dozens of content formats for translation. Smartling's Global Delivery Network translates websites without code interference, functioning like a translation proxy for site delivery.

Dynamic Content detection allows automatic updates for webpages or blog posts in native languages. Continuous Localization enables automatic updates and translation of new content. This helps teams save time, but buyers should confirm their CMS, support tools, and code repositories are supported before implementation.

Smartling’s CAT Tools and Linguist Experience

Smartling's built-in editor uses CAT technology for translation. In the editor, translators see strings, translation memory matches, glossary terms, and visual context where available. Smartling provides visual context for translators to view localized text in situ.

The system follows a traditional segment-based model: reuse existing words, enforce consistency, and reduce editing where possible. AI translation generally appears as machine translation suggestions that require post editing by translators.

By contrast, LILT’s adaptive AI updates suggestions as linguists edit across the document, which can reduce repeated corrections and make the workspace more user friendly for high-volume teams.

Translation Quality and Quality Assurance in Smartling

In Smartling, translation quality means accuracy, consistency, and adherence to brand voice defined in glossaries and style guides. Smartling's LQA tools monitor translation quality automatically, and Smartling's LQA Agent evaluates translations against quality thresholds.

Smartling can support MQM-style evaluation, scorecards, and dashboards. LQA Agent agrees with human reviewers 90% of the time, and Smartling's AI translation achieves 99% accuracy on severe errors, according to Smartling materials. Smartling enforces brand standards across 30+ locales with Style Rules.

Project managers tune QA rules based on errors, select reviewers, and manage feedback loops. High translation quality comes from strong terminology, clear review stages, and trained professional linguists.

AI Translation and Smartling’s Approach to Automation

Smartling's AI translation technology improves accuracy and speed. Advanced AI translation solutions utilize brand terminology for improved fluency. Smartling's AI adapts translations for regional variants automatically.

In practice, AI is layered on top of a classic TMS. Project managers still design workflows, and linguists still deliver final quality. Smartling may route content to different MT engines or apply automatic flags based on content type.

LILT takes a different approach: adaptive AI learns continuously from linguist corrections, improving future suggestions for the same brand. Buyers should ask whether self-improving AI matters for their long-term costs, review cycles, and quality curve.

Smartling as a Translation Management System

A translation management system centralizes multilingual content, workflows, vendor collaboration, and reporting. Smartling is strong where teams need granular workflow design, permissions, and control across languages.

Smartling provides in-depth analytics for localization projects. Real-time tracking of project progress is available through a dashboard in Smartling. Leadership can review job status, spend, throughput, vendor performance, and basic quality outcomes by language.

Smartling sits in the broader translation management category with platforms like LILT, but the emphasis is different: Smartling manages the process; AI-first systems increasingly automate translation decisions inside the work itself.

Project Managers, Roles, and Governance

A Smartling project manager typically creates jobs, assigns vendors, monitors progress, resolves issues, and manages review. Linguists, reviewers, legal teams, and regional stakeholders can receive controlled access depending on the contract.

This governance suits complex organizations that need approval chains, legal review, or regional marketing sign-off. For example, a global travel brand such as british airways may care as much about brand voice and compliance as raw speed.

When evaluating Smartling translation, map dashboards and permissions to your internal compliance needs. Strong control is valuable, but too many steps can slow localized content.

Smartling vs. AI-First Platforms Like LILT

Smartling and LILT both aim to improve translation quality and reduce time to market. The difference is how each platform uses technology.

Smartling relies heavily on workflow automation, translation memory, terminology, and configured QA. LILT combines translation management with adaptive AI that learns from human corrections in real time.

That difference affects translator productivity, costs, and how quickly a system learns brand voice across large volumes of multilingual content.

Translation Quality and Adaptivity

Smartling quality improves as memories grow, glossaries mature, and processes become stricter. That is effective for stable content and established terminology.

LILT’s adaptive AI updates suggestions as professional linguists type, learning preferred terminology, phrasing, and style during the actual job. Over time, this can mean fewer edits per segment.

For dynamic content such as product releases, support articles, and frequent campaigns, adaptive AI can shorten review cycles. During any evaluation, compare edit distance, review rounds, severe errors, and final quality scores.

Workflow, Productivity, and Translator Experience

Smartling excels at orchestrating complex workflows with routing rules, vendor collaboration, and structured review. LILT emphasizes translator productivity by accelerating each sentence, not only the surrounding management process.

A fair pilot should include both project managers and translators. Run the same content through both platform styles, then compare throughput, post editing effort, quality assurance time, and words completed per hour.

When Smartling Translation Fits, and When to Consider Alternatives

There is no single best localization platform. The right choice depends on content volume, content risk, internal process, and AI maturity goals.

Smartling often fits companies needing detailed governance, many vendors, pre built integrations, and strict review. Smartling's starting cost is $0.005 per word, while translation typically costs around $0.10 per word. Smartling's pricing is volume-based for predictable budgeting, and Smartling offers customized plans based on localization needs. Average cost savings with Smartling is 70% in the first year, according to vendor claims.

Teams often evaluate LILT when they want adaptive AI, faster review, and lower manual maintenance across changing content. Product launches, knowledge bases, software updates, and campaign-heavy marketing teams are common examples.

Think beyond per-word costs. The better question is which system will scale, deliver high quality translations, and reduce long-term friction for your customers and clients.

How LILT Complements or Replaces Legacy TMS Workflows

Some enterprises keep an existing TMS while using LILT as an ai translation and linguist productivity layer for selected content streams. Others migrate to LILT to centralize translation management, terminology, analytics, and adaptive AI in one environment.

LILT integrates with major CMSs, code repositories, and support systems, similar to traditional TMS tools, but with AI-centric workflows. Its analytics help teams track AI performance, translator productivity, and quality trends.

Build your business case around time-to-publish, error rates, review cycles, and cost per approved word-not only feature checklists.

FAQ

Is Smartling a translation management system or just a CAT tool?

Smartling is a full translation management system with an integrated browser-based CAT tool. The TMS layer handles intake, routing, permissions, and reporting, while the CAT tool is where translation and editing happen.

How does Smartling’s AI translation compare to LILT’s adaptive AI?

Smartling typically uses MT engines and automation features layered onto classic workflows. LILT’s adaptive AI learns from translator edits continuously, improving translation quality over time for each brand.

Can I use Smartling and LILT together?

Yes, some organizations use multiple tools during transitions or for different content streams. Feasibility depends on source systems, APIs, connectors, and how teams want to manage handoffs.

What should project managers focus on when evaluating Smartling?

Focus on workflow flexibility, integration coverage, QA depth, dashboard usability, and translator experience. Track turnaround time, review rounds, error types, and manual effort during pilots.

How does LILT support translation quality for regulated content?

LILT combines adaptive AI with expert linguists, terminology management, and rigorous quality assurance workflows. Teams can add legal, medical, or internal review steps where high-risk content requires additional control.